How CEOs Can Keep Their Analytics Programs from Being a Waste of Time

Despite billions of dollars invested in big data and analytics, the simple truth is that most projects and programs fail to meet expectations. And we have figured out why: analytics forces changes on the C-suite that the CEO has to anticipate and manage, but many don’t.

From how we choose presidents to what movies we choose to watch, big data and analytics have become integral parts of our lives. But for too many companies, analytics is an unsolved puzzle with the pieces flung all over the floor. In research spanning 20 years, we closely examined 36 companies in eight industries to find out why companies are struggling. The findings show that fewer than half of analytics programs met initial return-on-investment (ROI) goals.

But poor ROI is only part of the story. Other signs that something is wrong included:

A high level of frustration with analytics projects among leaders

More than half of senior executives experienced a backlog of at least two years on critical new analytics applications

These are not minor problems, and the fixes are not easy. While CEOs typically understand the transformative potential of big data/analytics, they often do not consider the flip side of the coin — that analytics efforts unleash forces within an organization that can threaten the analytics program itself. These forces must be understood and managed for the entire initiative to succeed. The CEO has to work on four things:

Actively manage C-suite dynamics. Every C-suite maintains a delicate balance of power. When the CEO assigns ownership of analytics, that executive will command bigger budgets and more time on the board agenda and will oversee a powerful new pool of resources. Simultaneously, other executives will not only experience a loss of influence but also feel vulnerable. This vulnerability frequently compels traditionalists to resist analytics.

CEOs must anticipate this reaction. Start by talking openly about the journey and the inherent sense of vulnerability executives are bound to feel as the business model changes. Being transparent about the level of expected change and the different skills executives will need to manage the change gets the dialogue above the table. Finally, the CEO must identify the executives most vested in the status quo and proactively manage their resistance — up to and including weeding out the obstinate ones.

Choose the right analytics leader. Seemingly, the simple solution would be to just hire a highly technical person or an analytics evangelist who preaches the potential of big data. But that is not always the case. This is about more than technology. While technical competence is a starting point, the CEO should choose an analytics leader with three distinct qualities: (1) an ability to collaborate, have his or her ideas shaped by others and to champion the ideas of others; (2) an understanding of how the enterprise currently operates and a vision for how analytics could drive the company to a brighter, perhaps radically different, future; and (3) the hunger to create an environment of discovery, where the data is allowed to shape the future of the company. The high turnover rate among CAOs mentioned earlier is a clear signal that finding the right analytics leader is a difficult task.

Challenge existing mental models. High-achieving executives have been shaped by the pivotal experiences of their careers, yet analytics requires executives to think beyond these mental models. The CEO must identify rigid modes of decision making among leaders, make it clear that the analytics era demands a new way of thinking, both individually and collectively, and guide them to that light.

Executives who are attached to the status quo and fear change will succeed in only one way: misdirecting the analytics initiative and perhaps killing it altogether. Ironically, this allows them to actually gain stature as the “innovators” are discredited and C-suite power shifts back to how it was.

Many CEOs underestimate the impact of mental models in the innovation process, often assuming that “thinking outside the box” exercises address the issue. As one financial services CFO told us, “Our mental models were so rigid that even how we thought about data itself needed to be challenged. [Information] had been a source of political capital — to be hoarded and primarily used to fight internal battles. We are only now coming to grips with the notion that the fate of the company is dependent on our collective and strategic use of information.”

Create an environment of rapid innovation. Successful analytics programs require a type of learning that few organizations are innately capable of. Analytics can enable breakthrough innovations but only if the environment supports open discovery and experimentation. If the analytics effort is anchored to traditional learning processes, it will not move fast enough to achieve meaningful change and competitive advantage. This “minimum velocity” at which insights must circulate to fuel innovation is widely misunderstood. Hampered by silos, incentives, and legacy behavior, most companies never approach it. A common sign of a low-velocity environment is an overreliance on problem-solving competitions, such as Kaggle. While these tools are invaluable and a crucial component of any program, they are just tools and, like any tool, can become a crutch if larger issues are not addressed.

Experimentation must be rewarded — something too few companies do. In the survey we conducted last year, we found that only 17% of companies tied innovation to compensation.

The rapid generation of big data over the past few decades has given rise to stunning capabilities — and there are no signs it will slow down. But in order for their companies to fully exploit them, CEOs must step up; they cannot abdicate leadership or delegate responsibility. The good news for the many companies struggling to optimize their big data/analytics investments is that they are not alone. The race for competitive advantage can still be won.

Chris McShea is a principal at EY, where he has worked with clients on the strategic use of analytics for over two decades.

Dan Oakley is an executive director in the Strategic Analytics practice of EY.

Chris Mazzei is EY’s global chief analytics officer and leads the efforts to embed analytics into EY’s service offerings across all lines of business.